Plot and fit distributions of variables

Histogram of Velocity of all

Log distribution, 0’s make up 3% of all data

CC.TotalData <- na.omit(TotalData)
head(CC.TotalData)
10^mean(log10(CC.TotalData$v[CC.TotalData$v>0]))
[1] 0.0348809
sd(log10(CC.TotalData$v[CC.TotalData$v>0]))
[1] 0.5467087

Now we’re going to plot each unique krill and their bimodality with a dip test (less than 0.05 is multimodality)

Starting to look at bimodality in the variables by merging the TotalData frame with the “tab” table

Now looking at turning angles

for (i in 1:length(ind)){
plot(CC.TotalData$turn.angle[CC.TotalData$D_V_T==ind[i]], log10(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]]),
            xlab = "Turn Angles",
     ylab = "Velocity",
          main = "") 
}

NA

save.image("~/Post-doc/Data/Total Merged Data File.RData")
---
title: "Checking Distribution for Variables"
output: html_notebook
---

Plot and fit distributions of variables

```{r}

load("C:\\Users\\nicoleh3\\Documents\\Post-doc\\Data\\Total Data Merged File (Sep 27 2021).Rda")

hist(log10(TotalData$v),
     xlab = "Velocity (Log^10 mm/s)")

```

Histogram of Velocity of all

Log distribution, 0's make up 3% of all data

```{r}
CC.TotalData <- na.omit(TotalData)
head(CC.TotalData)
10^mean(log10(CC.TotalData$v[CC.TotalData$v>0]))
sd(log10(CC.TotalData$v[CC.TotalData$v>0]))

```
Now we're going to plot each unique krill and their bimodality with a dip test (less than 0.05 is multimodality)

```{r}
ind <- unique(TotalData$D_V_T)
print(ind)
length(ind)
library(diptest)
library(DescTools)

tab <- matrix(data = NA, nrow = 135, ncol =5, byrow = T)
colnames(tab) <- c('dip.test', 'skew', 'mean.velocity', 'sd.velocity', 'Ind')

tab <- as.data.frame(tab)
tab$Ind <- ind
mean.vel <- NULL
sd.vel <- NULL
d.v <- NULL
s.v <- NULL

for (i in 1:length(ind)){
mean.v <- mean(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]])
sd.v <- sd(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]])

mean.vel <- rbind(mean.vel, mean.v)
sd.vel <- rbind(sd.vel, sd.v)


vels <- (CC.TotalData$v[CC.TotalData$D_V_T==ind[i]])
vels <- log10(vels[vels>0])
d <- dip.test(vels)
d.p <- d$p.value
d.v <- rbind(d.v, d.p)

s <- Skew(vels)
s.v <- rbind(s.v, s)
##}

##ind <- unique(CC.TotalData$D_V_T)

##for (i in 1:length(ind)){
 hist(log10(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]]),
     breaks = 50,
     xlab = "Velocity (Log^10 mm/s)",
     main = ind[i],
     sub = d.p)  ## change to d.p or s to print the dip test or skew value as the title instead
}

tab$skew <- s.v
tab$dip.test <- d.v
tab$mean.velocity <- (log10(mean.vel))
tab$sd.velocity <- (log10(sd.vel))
tab
write.table(tab, file = "~/Post-doc/Data/dip.test.skew.vels.csv", sep = ",", col.names = TRUE)

plot(tab)


head(TotalData)
str(TotalData)
TotalData$Flow.rate <- as.factor(TotalData$Flow.rate)
TotalData$Chlorophyll <- as.factor(TotalData$Chlorophyll)

library(ggplot2)
ggplot(TotalData,aes(x=Flow.rate, y=turn.angle, fill=Chlorophyll))+
  geom_boxplot(notch=F, notchwidth=0.3,outlier.shape=1,outlier.size=2, coef=1.5)+
  theme(axis.text=element_text(color="black"))+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4))+
  theme(panel.grid.minor=element_blank())+
  labs(size= "",x = "Flow Rate (cm/s)", y = "Turn angle (degrees)", title = "               Light")+
  scale_fill_manual(values=c("greenyellow", "green","green1", "green2", "green3", "green4"),name = "Chlorophyll (mg/L)",
                    labels=c("0", "4.6", "6.1", "7.6", "13.5", "19"))+
  facet_grid(~Light, scales = "free_x", space = "free")
```


Starting to look at bimodality in the variables by merging the TotalData frame with the "tab" table
```{r}
##agregating Complete cases of TotalData so we can merge it with tab data

AGG_TD <- aggregate(TotalData, by = list(TotalData$D_V_T), FUN = mean)
head(AGG_TD)
AGG_TD <- AGG_TD[ -c(2:3, 8:10) ]
colnames(AGG_TD) <- c("Ind", "X", "Y", "Z", "Track", "Flow.Rate", "Chlorophyll", "Guano", "Light", "dx", "dy", "dz", "d", "vx", "vy", "vz", "v", "heading", "pitch", "turnangle.xy", "turnangle.yz", "turn.angle")
head(AGG_TD)
tail(AGG_TD)


tab_AGG <- merge(AGG_TD, tab, by = "Ind")
head(tab_AGG)
str(tab_AGG)
tab_AGG$Flow.Rate <- as.factor(tab_AGG$Flow.Rate)
tab_AGG$Chlorophyll <- as.factor(tab_AGG$Chlorophyll)
tab_AGG$Guano <- as.factor(tab_AGG$Guano)
tab_AGG$Light <- as.factor(tab_AGG$Light)


freq <- table(tab_AGG$Flow.Rate, tab_AGG$Chlorophyll)
print(freq)
prob <- prop.table(freq) ##Relative Frequency Table
print (prob)

 ##starting to plot the dip test and skew in the variables
plot(tab_AGG$Flow.Rate, tab_AGG$dip.test, xlab = "Flow Rate (cm/s)", ylab = "Dip Test (p.value)")
plot(tab_AGG$Flow.Rate, tab_AGG$skew, xlab = "Flow Rate (cm/s)", ylab = "Skew Test (p.value)")
plot(tab_AGG$Chlorophyll, tab_AGG$dip.test, xlab = "Chlorophyll (mg/L)", ylab = "Dip Test (p.value)")
plot(tab_AGG$Chlorophyll, tab_AGG$skew, xlab = "Chlorophyll (mg/L)", ylab = "Skew Test (p.value)")

library(ggplot2)
ggplot(tab_AGG,aes(x=Flow.Rate, y=skew, fill=Chlorophyll))+
  geom_boxplot(notch=F, notchwidth=0.5,outlier.shape=1,outlier.size=2, coef=1.5)+
  theme(axis.text=element_text(color="black"))+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4))+
  theme(panel.grid.minor=element_blank())+
  labs(size= "",x = "Flow Rate (cm/s)", y = "Skew (p value)", title = "")+
  scale_fill_manual(values=c("greenyellow", "green","green1", "green2", "green3", "green4"),name = "Chlorophyll (mg/L)",
                    labels=c("0", "4.6", "6.1", "7.6", "13.5", "19"))  
 ## + facet_grid(~Light, scales = "free_x", space = "free")

```

Now looking at turning angles

```{r}
TotalData$turn.anglexy <- atan2(TotalData$X, TotalData$Y)
TotalData$turn.angleyz <- atan2(TotalData$Y, TotalData$Z)


lth <- dim(TotalData)[1]
dx1 <- TotalData$dx[1:(lth-1)]
dx2 <- TotalData$dx[2:lth]
dy1 <- TotalData$dy[1:(lth-1)]
dy2 <- TotalData$dy[2:lth]
dz1 <- TotalData$dz[1:(lth-1)]
dz2 <- TotalData$dz[2:lth]
D <- (dx1*dx2)+(dy1*dy2)+(dz1*dz2)
d1 <- sqrt(dx1^2 + dy1^2 +dz1^2)
d2 <- sqrt(dx2^2 + dy2^2 +dz2^2)

dd <- D/d1/d2
hist(acos(dd)/pi*180)

TotalData$turn.angle <- c(NA, acos(D/d1/d2))/pi*180
CC.TotalData <- na.omit(TotalData)
head(CC.TotalData)
tail(CC.TotalData)
str(CC.TotalData)
CC.TotalData$Flow.rate <- as.factor(CC.TotalData$Flow.rate)
CC.TotalData$Chlorophyll<- as.factor(CC.TotalData$Chlorophyll)

ind <- unique(CC.TotalData$D_V_T)

for (i in 1:length(ind)){
hist(CC.TotalData$turn.angle[CC.TotalData$D_V_T==ind[i]],
       breaks = 50,
     xlab = "Turn Angles",
     main = "") 
}

plot(CC.TotalData$Flow.rate, CC.TotalData$turn.angle, main = "", xlab = "Flow Rate (cm/s)", ylab = "Turn angle (degrees)")
plot(CC.TotalData$Chlorophyll, CC.TotalData$turn.angle, main = "", xlab = "Chlorophyll (mg/L)", ylab = "Turn angle (degrees)")

```



```{r}
for (i in 1:length(ind)){
plot(CC.TotalData$turn.angle[CC.TotalData$D_V_T==ind[i]], log10(CC.TotalData$v[CC.TotalData$D_V_T==ind[i]]),
            xlab = "Turn Angles",
     ylab = "Velocity",
          main = "") 
}

```


```{r}
save.image("~/Post-doc/Data/Total Merged Data File.RData")

```



